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Record W2744718186 · doi:10.5144/0256-4947.2017.297

Isometric muscle fatigue of the paravertebral and upper extremity muscles after whiplash injury

2017· article· en· W2744718186 on OpenAlexaboutno aff
Pejana Rastović, Marija Definis Gojanović, Marina Berberović, Marko Pavlović, Josip Lesko, Gordan Galić, Maja Pandža

Bibliographic record

VenueAnnals of Saudi Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWhiplashFamily medicinePoison controlMedical emergency

Abstract

fetched live from OpenAlex

BACKGROUND: Whiplash-associated disorders (WAD) result from injury of neck structures that most often occur during traffic accidents as a result of rapid acceleration-deceleration. The dominant symptoms manifest in the musculoskeletal system and include increased fatigue. Because of the frequency of whiplash injuries, a simple, cheap and useful diagnostic tool is needed to differentiate whiplash injury from healthy patients or those faking symptoms. OBJECTIVES: To determine muscle fatigue in patients with whiplash injury in six body positions. DESIGN: Analytical cross-sectional study. SETTING: Emergency center, university hospital. PATIENTS AND METHODS: We studied patients with whiplash injury from vehicular traffic accidents who presented to the emergency center within 6 hours of sustaining the injury. We determined whiplash injury grade according to the Quebec Task Force (QTF) classification and measured isometric muscle endurance in six different body positions. Control subjects for each patient were matched by age, gender and anthropomorphic characteristics. Cut-off values were determined to distinguish patients with whiplash injury from controls and for determination of injury grade . MAIN OUTCOME MEASURE(S): QTF grade, time to muscle fatigue in seconds. RESULTS: From September 2013 to September 2016, we enrolled 75 patients with whiplash injury and 75 matching control subjects. In all six positions, the patients with whiplash injury felt muscle fatigue faster than equivalent controls (P < .05) and the time to onset of muscle fatigue decreased with increasing injury grades in all six positions. Assignment to the patient or control group and to injury grade could be predicted with more than 90% accuracy on the basis of time to muscle fatigue. The most efficient position was the highest injury grade, by which 99.9% of the patients were accurately categorized. Isometric muscle endurance correlated with whiplash injury grade in all six positions (P < .01). CONCLUSION: Under clinical conditions, muscle endurance and the appearance of isometric muscle fatigue during testing can be a useful indicator of whiplash injury and grade. LIMITATIONS: The size of the sample was small. An objective parameter such as electromyography is needed to confirm isometric muscle fatigue.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.054
GPT teacher head0.352
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2017
Admission routes1
Has abstractyes

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